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Nonlinear Predictive Modeling of MHC Class II-Peptide Binding Using Bayesian Neural Networks
Methods for predicting the binding affinity of peptides to the MHC have become more sophisticated in the past 5–10 years. It is possible to use computational quantitative structure-activity methods to build mo...
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Application of Neural Networks to Large Dataset QSAR, Virtual Screening, and Library Design
In the past decade, it became clear that some fundamental problems were arising in drug discovery. It was becoming harder to find new chemical entities with substantial advantages over existing drugs. Conseque...